ADNOC is moving from pilots to production with ENERGYai, a first-of-its-kind agentic AI platform co-developed with SLB and AIQ. This article explores how the Abu Dhabi energy pioneer is embedding autonomous AI across geology, seismic exploration, and reservoir modelling to accelerate decision-making, cut cycle times, and unlock competitive advantage in the global energy transformation.
The rise of artificial intelligence (AI) and its massive energy needs is presenting governments and industries alike with supply challenges and opportunities that are reshaping the entire energy ecosystem and geopolitical landscape.
SLB and AIQ are co-creating and implementing agentic AI workflows in geology, seismic exploration, and reservoir modelling for the Abu Dhabi-based energy pioneer
ADNOC is moving from pilots to production, with a homegrown agentic artificial intelligence (AI) platform designed to automate large portions of subsurface work including geology, seismic explorations, and reservoir modelling - work that is traditionally done by geoscientists and engineers, and that spans weeks and months.
AIQ, the Abu Dhabi-based AI developer and SLB, the global oilfield services company, are co-developing ENERGYai, a first-of-its-kind agentic AI solution to be rolled out across ADNOC’s geology, seismic, and reservoir workflows. The first deployments are slated for the fourth quarter of 2025. Early tests showed a tenfold speed-up in seismic interpretation and a 70% precision gain, which are impressive figures in a discipline where cycle time is money.
The partnership formalises SLB’s role as a key implementation partner alongside Microsoft and G42, and will be delivered via SLB’s Lumi data and AI platform, designed to simplify access to subsurface and operations data, and scale AI safely across large enterprises.
What does agentic AI mean?
Agentic AI refers to systems capable of autonomous decision-making, planning, and executing complex, multi-step tasks with minimal human oversight. ENERGYai will help ADNOC optimise upstream operations, including development planning, real-time process monitoring, and forecasting.
For ADNOC, the impetus behind developing ENERGYai is both technological and strategic. As energy and AI converge, the company aims to harness the trend for competitive advantage, ensuring a more secure, inclusive and sustainable future.
What makes ENERGYai different?
ENERGYai is trained on petabytes of ADNOC’s proprietary subsurface data spanning decades. It is designed to interpret seismic data, update reservoir models, or recommend well trajectories while calling on large language models (LLMs) for reasoning and human-readable explanations.
“ENERGYai marks a major milestone in ADNOC’s journey to be the world’s most AI-enabled energy company, and a key enabler of the global energy transformation. It will be a powerhouse for value creation and sustainable energy production, and will leverage petabytes of data to better empower our people and unlock innovative solutions across our value chain.”
- His Excellency Dr Sultan Ahmed Al Jaber, UAE Minister of Industry and Advanced Technology and ADNOC Managing Director and Group CEO"
ENERGYai was launched at ADIPEC 2024 and progressed through a 90-day proof-of-concept phase, before moving to scaled deployment.
A multi-year contract underlines the company’s intent to industrialise the technology.
SLB’s Lumi matters here because data, not models, is usually the chokepoint for AI agents. Lumi was launched in September 2024 as an open, secure, and modular platform that exposes high-quality subsurface and operations data, and supports physics-based and generative models. In short, it gives the agents something reliable to work with.
Why does this matter beyond ADNOC?
Two forces make ADNOC’s ENERGYai development timely. First, the upstream oil and gas services market is vast and operationally complex. Even small percentage productivity gains matter. To put things in perspective, the global expenditure on oil & gas and energy developments are likely to average more than US$920 billion annually during 2022-2028, according to a study by Rystad Energy. Second, AI itself is becoming an energy story; the power demand of AI data centres is forcing energy suppliers to get sharper on efficiency and low-carbon electrons.
For ADNOC, agentic AI serves two priorities: speed and certainty. Faster seismic interpretation compresses appraisal cycles, continually updated reservoir models support more confident drilling decisions, and automated monitoring sharpens production optimisation and surveillance. The company’s autonomous AI push aims to lift operational efficiency and improve production forecasting, benefits that, if proven at scale, tend to show up in lower unit costs and potentially, lower emissions intensity per barrel.
From pilots to field rollouts
Lumi’s pitch centres on trustworthy data and controlled deployment. ENERGYai’s agents are trained for specific, governed workflows rather than left to operate freely. The real test will be when AIQ and SLB move from limited assets to rollouts across fields with very different geology and legacy systems.
The direction of travel is clear. AI’s enterprise-wide productivity upside is vital. McKinsey pegs the broader corporate AI value at up to US$4.4 trillion annually and upstream remains data-rich but decision-constrained. In that context, ADNOC’s push to embed agentic AI in core subsurface workflows looks promising for the giant energy player that wants to compete on speed, safety, and carbon.